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Inheritance of Economic Traits in the Regional Cornell Control Population1
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EGG QUALITY VARIATION
able genetic variation in albumen quality loss. Our genetic correlations indicated that early sexual maturity is associated with lower egg quality. Similarly, consistent negative correlations between egg production and egg quality were found. REFERENCES
Inheritance of Economic Traits in the Regional Cornell Control Population 1 STEVEN C. K I N G 2
Poultry Research Branch, Animal Husbandry Research Division, ARS, Regional Breeding Laboratory, Purdue University, Lafayette, Indiana
Poultry
(Received for publication September 19, 1960)
K
NOWLEDGE of genetic parameters is useful in designing efficient breeding systems. Estimation of genetic parameters raises the problem of suitable material as a source of data. Until recently, genetic pa1 This investigation was conducted as a portion of the cooperative research of the NC-47 Regional Poultry Breeding Project, entitled, "Evaluation of Breeding Systems for Chickens." 2 Present address: Poultry Research Branch, Animal Husbandry Research Division, Beltsville, Maryland.
rameters in poultry populations have been estimated from data collected from inbred lines or selected populations. Estimates obtained from inbred lines have required correction factors in order to compensate for changes in genetic variance due to inbreeding. In addition, few of these inbred lines were developed without considerable natural and/or artificial selection. Estimates obtained from non-inbred populations under artificial selection have ignored, for the most part, the bias which may result from
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Eisenhart, C , 1947. The assumptions underlying the analysis of variance. Biometrics, 3 : 1-21. Goodman, B. L., and G. F. Godfrey, 1955. Genetic, phenotypic and environmental correlations between some egg quality traits and egg production and hatchability. Poultry Sci. 34: 1197. Henderson, C. R., 1953. Estimation of variance and covariance components. Biometrics, 9: 226-252. Jerome, F. N., C. R. Henderson and S. C. King, 1956. Heritabilities, gene interactions, and correlations associated with certain traits in the domestic fowl. Poultry Sci. 35: 995-1013. Johnson, A. S., and E. S. Merritt, 1955. Heritability of albumen height and specific gravity of eggs from White Leghorns and Barred Rocks and the correlations of these traits with egg production. Poultry Sci. 34: 578-587.
King, S. C , 1961. Inheritance of economic traits in the Regional Cornell Control population. Poultry Sci. 40: 975-986. King, S. C, J. R. Carson and D. P. Doolittle, 1959. The Connecticut and Cornell randombred populations of chickens. World's Poultry Sci. J. 15: 139-159. King, S. C , and G. 0. Hall, 1955. Egg quality studies at the New York Random Sample Test. Poultry Sci. 34: 799-809. King, S. C , and C. R. Henderson, 1954. Variance components analysis in heritability studies. Poultry Sci. 33 : 147-154. Kyle, W. H., and J. D. Mitchell, 1958. Heritability of the change in egg quality during storage. Poultry Sci. 37: 1219. May, K. N., F. J. Schmidt and W. J. Stadelman, 1957. Strain variation in albumen quality decline of hen's eggs. Poultry Sci. 36: 1376-1379. McClary, C. F., and G. E. Bearse, 1956. The genetic correlation of albumen quality in fresh and stored eggs. Poultry Sci. 35: 1157. Mueller, W. J., 1959. Factors affecting the quality loss in egg albumen during storage. Poultry Sci. 38: 843-846. Yao, K. T. S., 1958. Egg interior quality of purebred, inbred, incross and incrossbred chickens. Poultry Sci. 37: 1254-1255.
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and Mitchell (1959) and King et d, (1961) meet the necessary assumptions for a variance components analysis. The purpose of this paper is to report the results of our analysis of data collected from the Regional Cornell Control population of White Leghorns, which is maintained at the Regional Poultry Breeding Laboratory, Lafayette, Indiana. Several of the economic traits of importance in egg production stocks were analyzed. MATERIALS AND METHODS Many estimates of genetic parameters in the domestic fowl have been reported in the literature, but relatively few have resulted from experimental designs which enabled estimates of sire by dam interactions to be made. Hazel and Lamoreux (1947) published estimates of dominance as did Jerome, Henderson and King (1956) much later. Since then Smith and Jaap (1957) have indicated some of the problems involved in achieving reliable estimates. Jaap collected data from diallel sets of matings, each of which yielded one degree of freedom for the sire by dam interaction mean square. He later tried, with some success, triallel sets in order to build up degrees of freedom at a faster rate and to achieve estimates having narrower confidence limits. Devising a mating scheme for animals, which will result in data that fit a neat analysis of sire by dam interaction effects, is no small problem. It is a simple matter with economic species of farm animals and birds to mate a single male to several females, either naturally or through artificial insemination. However, the physiology of reproduction of the female of these species make it extremely difficult to mate a female to several males at the same time and still maintain the identity of the male parent. It is possible to accomplish this feat through the use of a different marker gene for each male parent, but this, for all
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the use of selected parents in the typical variance components analysis. Correction for the reduction of genetic variance in selected parents by the use of adjustment factors is very difficult or even not feasible with the accuracy one desires. Even when selection is for only one or a few traits, correlated responses may introduce some bias into the estimates of the parameters of traits not selected. While it is not intended to imply that genetic parameters estimated in selected populations do not have value, the usual variance components analysis assumes unselected parents mated at random. Further, an understanding of the fundamental genetic forces coming into play would appear to be somewhat easier to achieve without the complicating effects of selection and inbreeding. The several randombred control populations, which have been established at various institutions, furnish an excellent opportunity to secure data from offspring of unselected parents. Another advantage of utilizing material of this kind is the opportunity of observing changes in genetic parameters when a subsample of the control population is put under a selection system. This has obvious advantages over trying to extrapolate backwards, in order to determine what the genetic parameters might have been in a selected population before selection began. Estimates of genetic parameters have been published from research with pilot organisms by Chapman (1946), Robertson and Reeve (1952), Clayton, Morris and Robertson (1957), Bell and Moore (1958) and Martin and Bell (1960), to name a few, in which the data seem to satisfy the assumptions required in order to make an analysis of variance. With poultry as the experimental animal, only the data used by Smith and Jaap (1957), Jaap and Smith (1959), Kyle and Mitchell (1958), King
KING
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T A B L E 1.—Example of mating plan showing the sire by dam subclass totals (same as sire by dam by shift totals) Dams/ Sires 1 2 3 4 5 O 7 8 Sire totals
1
l
Xni X112 X213
7
L
J
5
X231 X123 X124 X225
X234 X135 X136
X21S X.2..
X.3..
Dam totals
X246 X147 X148
X . . 1. X . .Z. X. .3. X..4. X..5. X. .6. X . .7. X. .8.
X.4..
X...
X242
X227
X.I..
i *
Shift t o t a l s = X I . . . a n d X 2 . . .
ing procedure was utilized, in which the same 50 males and 250 females were mated in two shifts, but a different randomization each shift was used to assign each male his 5 female mates. Thus, each male was mated to a total of ten females and each female was mated to two cockerels during the breeding season. In order to illustrate the mating plan and facilitate the presentation of the method of analysis utilized, an example is presented in Table 1 showing the smallest subclass totals. Note particularly that sire by dam subclasses are identical with sire by dam by shift subclasses, since a dam can be mated to only one sire at a time and still maintain the identity of the male parent. • Eggs for setting were saved for a two week period and pedigreed to both dam and sire. A minimum of two weeks elapsed from rerandomization of matings for the second shift and the beginning of egg saving again. In 1957 there was a period of seven weeks between first and second shift hatches, while in 1958 this period between shifts was four weeks. Enough pullets were banded so that approximately two progeny per dam could be housed in each shift. Traits considered in this paper include age at first egg, percent hen day egg production to January 1 (approximately 36-40
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practical purposes, precludes the collection of data from a closed flock. The domestic fowl is one of the few economic species in which it is possible to arrange successive matings with a rather short span of time elapsing between matings and still maintain the identity of the parents. Hutt and Cole (1955) describe procedures for reducing this time interval between matings, which result in relatively few paternity errors. Unfortunately, the device of shifting sires results in the elapse of approximately four weeks between hatches when eggs are saved two weeks before setting. Data collected from progeny hatched on different hatch dates may be influenced by environmental differences between hatches and also by genotype by environment interactions. The complexity of the statistical analyses can be kept to a minimum by saving eggs two weeks before setting, thus assuring that most dams have progeny in each hatch or shift. It is obvious that mating each dam to more than two or three sires will result in an extended series of shifts, each at least four weeks apart. Thus, the greater the number of sires mated to each dam, the more likely is the prospect of serious shift by dam interactions becoming confounded with sire by dam interactions. The genetic parameter estimates reported in this paper were obtained by analysis of data collected on pullet flocks of the Regional Cornell Control population hatched in 1957 and 1958. This population was established as a replication of the Cornell Randombred Control population in 1956, when pedigreed hatching eggs were obtained. Details on the development and maintenance procedures utilized for this population may be found elsewhere (King, Carson and Doolittle, 1959). The pullets from which these data were collected were the progeny of at least 50 single male matings each year. A sire shift-
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TABLE 2.—Typical analysis of variance for sire'Kshift or hatch interaction Source Shift or hatch Sires Shift & Sires Dams w/n sires & shift Fullsibs
E(d. f.)
Actual d. f.
a —I s— 1 (a-l)(s-l) as(d — 1) ad(n-l)
1 50 48 197 490
E(m. s.)-\-kwtr?-\-ki\Oa' oe2+kl(ra2+h
£i = 2.45, ^ 2 = 2.86
ls.+ah+Si+dj-\-{sd)ij-\&h ijk
where /x is common to all observations, ah to all pullets in the hth shift (also hatch in this case, since there is only one hatch per shift), Si to all observations from the ith sire, dj to all records made by progeny of the j t h dam, {sd)ij to all records made by full sib progeny of the ith sire and j t h dam. Peculiar to each observation is the random error eujk- I t is assumed t h a t except for n, all elements of the model are uncorrelated variables with zero means and variances
period of seven weeks elapsed between shifts or hatches. If such an interaction variance exists in our data, it would have the greatest opportunity to express itself when the time difference between hatches was greatest, there being a greater likelihood of a significant hatch effect. The same experimental plan and set of data were utilized, but a different statistical model was employed. This was possible because of the unique nature of the breeding program used in the Regional Cornell Control flock. For this analysis the model, Yijki =
ii-\-ai+Sj-\-djkJr{as)ij+eijki
was assumed, where n is common to all observations, ff; to the tth hatch or shift, Sj to t h e j t h sire, djk to the kih dam within the j t h sire, (as)a to the interaction between the i t h hatch and j t h sire and e^u is the random error associated with each individual observation. Note t h a t under this model, any interaction between sire and dam,
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weeks of age) and at 72 weeks of age, 32 week body weight, 32 week egg weight and albumen score in June. An analysis of fresh and stored albumen quality at 32 weeks of age was presented in King et al. (1961). The statistical analyses utilized in this paper were based on the assumption of the linear model:
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TABLE 3.—Mean squares for testing significance of shift by sire interaction for several traits Dam w/n sires
Trait
Shift by sires
19.42 30.59 40.64 56.65 20.09 5.18
Haugh unit loss % Stored of fresh H. U. Haugh units, fresh Haugh units, stored Egg weight Total eggs (12 days)
16.54 22.60 38.27 37.08 19.10 4.25
and the coefficients of their expectations. Since high speed electronic computer equipment was available, the expectations in terms of sums of "squares were utilized. These were equated to the sums of squares and upon solving, the resulting equations yielded estimates of ju2, aj, o's2, a£, usi and o-„2. The discussion presented in King et al. (1961), pertaining to genetic parameters contained in each of the foregoing variances, applies equally to this paper. As in that paper, the term dominance is utilized to describe the genetic variance in the sire by dam interaction even though some other non-additive variance may be present. RESULTS AND DISCUSSION
Heritability estimates, presented in Table 4, are given by trait, year and
TABLE 4.—Estimates of heritability, environment, variance and means
i2
Trait Age at 1st Egg
1957 1958 Av.
32 Wk. Egg Wt.
1957 1958 Av. 1957 1958 Av.
32 Wk. Body Wt.
% Prod, to Jan. 1
1957 1958 Av.
% Prod, to 72 Wks.* USDA Albumen Score—June*
1957 1957
0.33 0.19 0.26 0.63 0.58 0.60 0.67 0.57 0.62 0.14 -0.02 0.06 0.16 0.10
V
hi
hj
h*
0.62 0.52 0.57
0.11 -0.02 0.04 0.16 0.32 0.24 0.24 -0.03 0.10
0.45 0.66 0.56
5.11 5.76 5.44
0.08 0.11 0.10 0.00 0.43 0.21
15.27 13.07 14.17 0.216 0.277 0.246
4.02 lbs. 4.04 lbs. 4.03 lbs.
0.44 0.29 0.36 0.36
0.24 0.53 0.38
245.5 254.4 250.0
72.6 74.3 73.4
0.24 0.51
292.3 0.976
66.3 4.06
0.88 0.58 0.73 0.86 0.63 0.74 0.49 0.37 0.43 0.64 0.71
0.08
* Analyses were completed before data for these traits had been collected in 1959.
X
25.85 wks. 26.22 wks. 26.04 wks. 52.7 gr. 52.0 gr. 52.4 gr.
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mean square for dams within sires and shifts in order to make a valid test of significance. Results presented in Table 3 indicate that F ratios would be less than one for each trait analyzed for shift by sire interaction. Clearly, the assumption of no shift by sire interaction appears to be tenable in this set of data. It would appear to be quite reasonable, then, to assume that the shift by dam interaction would be similarly unimportant, although one must admit that maternal effects due to health differences among the dams conceivably could change between shifts. The high production of the breeder flocks would not indicate this to be the case in this experiment. Having demonstrated that our assumption of no shift by sire interaction appears to be valid and assuming the unlikelihood of a shift by dam interaction, let us return to further consideration of the analysis of variance procedure utilized in order to produce the required sums of squares and cross products. The assumptions outlined correspond to those of the Eisenhart (1947) Model II. Henderson's (1953) Method 1 is an appropriate procedure for computing the sums of squares
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TABLE 5.—Maternal effects Trait Age at 1st Egg 32 Wk. Egg Wt. 32 Wk. Body Wt. % Prod, to Jan. 1 % Prod, to 72 Wks. USDA Alb. Score
1957
1958
Av.
0.072 0.062 0.048 0.088 0.120 0.152
0.082 0.000 0.015 0.098
0.077 0.031 0.032 0.093 0.120 0.152
— —
parable to those published by Hazel and Lamoreux (1947) for body weight, b u t they found no maternal effect for sexual maturity, while our data resulted in an estimate of 7.7%. To our knowledge maternal effects have not been estimated by other investigators. Even though our estimates indicate t h a t maternal effects are small, the fact t h a t they were consistently present forces one to consider the consequences of their presence in a selection program. I t is of no little importance to know whether these maternal effects are due to genetic differences or chance environmental influences t h a t made some hens better dams than others. Selection based on dam family averages would be highly desirable in the instance of genetic differences, but if these differences are due to environmental effects, one would want to discount in some way those dams which appeared to be the best. These results are all the more surprising in an oviparous species. Everyone is familiar with the important effect the mother may have on her young in mammalian species, where the nutrition and protection may extend from a few weeks to m a n y months depending upon the species. Even after birth the mother m a y continue to exert a great influence on her offspring before it is weaned. In the domestic fowl the hen must be content to rely on what she included in the egg, because she ceases to have any further opportunity under today's commercial conditions. These small, but consistent, maternal effects, found for each of six important productive traits suggest a whole new field of research. Included in the knowledge we would like to have is the extent to which the environment of the mother m a y be modified to improve the performance of her progeny, the mechanisms by which maternal effects are passed through the egg to influence prog-
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source of the estimate of genetic variance. A rather striking feature of these estimates of heritability is the fact t h a t the estimates utilizing the dam's component of variance are in every instance as large as or larger t h a n the estimates from sire components. These results are of considerable importance, because the method of analysis has partitioned out a component of variance due to sire by dam interaction. Recall t h a t except for a limited number of estimates reported in the literature, the dam's component in the hierarchial classification includes any existing sire by dam interaction. With the exception of a few instances, the estimates of heritability from dams' components of variance has been higher than estimates from the sires' components of variance. Because of confounding it has been impossible to say whether maternal effects, sire by dam interactions or both have been responsible for the higher estimates from dams' components. Since our analysis partitioned out the sire by dam interaction variance component, we must conclude t h a t maternal effects were present for each trait in our analysis. While the fairly large differences between heritability estimates from sire and dam components make maternal effects appear to be of considerable magnitude, there is a multiplication factor of 4 included in the estimation procedure. Thus, the maternal effects, as shown in Table 5, are not particularly large even though they are fairly consistent in their presence. Our estimates of maternal effects are quite com-
KING
INHERITANCE OF ECONOMIC TRAITS
Egg weight, with an hs2 of 0.60, had a very high heritability and the estimate of 0.73 for hi indicated a small, but inconsistent, maternal effect. Surprising was the estimate of 0.24 for hsd2. With such a high estimate for additive variation one doesn't expect to see as much dominance, but it appears that the environment, accounting for only 10 percent of the total, had little to do with egg weight variation within hatches. Body weight showed the same high heritability as egg weight. It is evident
that the genetic variation is overestimated in the 1957 data, since one hardly can imagine a population in which the environment contributed nothing to body weight variation. Again there was some evidence for dominance effects for body weight, but the estimates weren't consistent between years. Heritability of egg production to January first was low and maternal effects appear to be at least as important in the total variation. Our hsi at 0.36 lends considerable support to the idea that dominance variation is a factor of importance in dealing with the inheritance of egg production. These results show quite clearly that the usual dams within sires nested classification may lead to gross overestimates of additive variation, when estimated by the &i component. When the production period was extended to 72 weeks of age, the results were about the same except that, astonishingly enough, maternal effects seemed to be even more important than for the part record. Whether this could come about through differences in maternal immunity passed through the egg and operating over a longer period or other mechanisms, we cannot say. Note that June albumen score, taken near the end of the laying year, exhibits a similar effect. The generally higher heritability estimates reported here as compared to those found in the literature deserve some comment. The Regional Cornell Control population was established with a broad genetic base. There has been no artificial selection and natural selection has been minimized. Inbreeding has been avoided, thus emulating an infinite population where inbreeding is zero. All these factors have tended to maintain the original high variability, thus one should expect higher heritabilities than those reported in the literature from various closed flocks and
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eny performance months later, and the extent and nature of the adjustments that may be required in selection programs. The average heritability for age at first egg, presented in Table 4, was 0.26 and 0.57 when estimated by hs2 and hi respectively. The difference of 0.31 can be explained by a maternal effect of only 0.077, discussed previously. It must be acknowledged that if sex-linked effects exist, they would cause the difference between hi and hi to be smaller, thus underestimating maternal effects. Since hi includes both additive variation and sex-linked effects, one is more or less forced to assume that hi is an upper limit for heritability in the additive sense and, until such time as conclusive evidence of sex-linked effects is forthcoming, that hi is the best point estimate available. Our 0.26 is identical with the average of published estimates reported by King and Henderson (1954), but in reality probably is an estimate of a higher parameter, because the earlier average included estimates that undoubtedly were inflated by maternal and dominance effects included in the estimation procedures. Apparently sexual maturity is but little influenced by dominance effects, however, since h3i was only 0.04 in our data with a small positive estimate the first year being partially offset by a slightly negative estimate the second year.
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S. C. KING TABLE 6.—Estimates of genetic, environmental and phenotypic correlations averaged overthe Z years
Age at 1st egg and 32 Wk. Egg Wt. 32 Wk. Body Wt. % Prod, to Jan. 1 % Prod, to 72 Wks. Haugh Units—Fresh
r*
Td
rsd
rCl
r?
0.78 0.50 -0.15 -0.17 0.40
0.13 -0.08 -0.80 -1.07 0.33
-2.05 -1.66 -0.25 1.73 -1.59
0.62 0.18 0.13 -0.68 0.41
0.13 0.04 -0.18 -0.23 0.23
0.33 -0.50 -0.24 0.30
0.57 -0.06 0.26 0.32
1.05 -0.35 0.21 -1.48
-0.40 0.78 0.03 1.18
0.40 -0.02 0.11 0.12
0.70 -0.01 0.03
0.07 0.33 0.31
-0.26 -0.32 -1.95
0.29 0.24 0.52
0.13 0.09 0.03
0.69 -0.33
1.11 -0.34
0.39 -0.38
0.49 0.21
0.64 -0.13
-0.30 0.34
-0.45 -0.20
0.69 1.53
0.00 -0.57
-0.06 0.02
32 Wk Egg Wt. and
32 Wk. Body Wt. and % Prod, to Jan. 1 % Prod, to 72 Wks. Haugh Units—Fresh % Prod, to Jan. 1 and % Prod, to 72 Wks. Haugh Units—Fresh % Prod, to 72 Wks. and Haugh Units—Fresh USDA Alb. Score
* rs is an estimate computed from sire covariances and variances, "n from dam covariances and variances, and fSd from sireXdam covariances and variances.
inbred lines established from these flocks, which had variation reduced by both selection and inbreeding. A survey of the genetic correlations reported in Table 6 lead one to the conclusion t h a t their estimation is far from satisfactory from the point of view of consistency. The situation doesn't appear to be quite as hopeless, if one remembers the previous discussion of maternal effects and the fact t h a t they are included in the d a m s ' component of variance. Certainly, there is no logical reason to believe t h a t correlations due to maternal effects must necessarily be of the same magnitude, or even of the same sign, as those due to additive variation. Also, it follows t h a t correlations due to dominance deviations need not be necessarily of the same magnitude or sign as those due to additive deviations. However, even after making
allowances for these considerations, it is evident from Table 6 t h a t correlations due to dominance effects often exceed the theoretical limits and to a lesser extent this is true for correlations computed from dams' components of variance and covariance. I n spite of these difficulties, there are some observations from which one m a y draw tentative conclusions or perhaps suggest the existence of certain trends. For the author, at least, consideration of the estimates of heritabilities in Table 4 has helped to interpret or rationalize the correlations presented in Table 6. Early sexual maturity appears to be associated with small egg size whether one is thinking in terms of genetic correlations due to additive effects or environmental effects; however, environmental effects played a large part in the relationship between
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32 Wk. Body Wt. % Prod, to Jan. 1 % Prod, to 72 Wks. Haugh Units—Fresh
INHERITANCE OF ECONOMIC TRAITS
Early sexual m a t u r i t y was associated with small body size when the genetic correlation was estimated by f„ but fd was —.08, indicating t h a t maternal effects may have been in the opposite direction. The phenotypic correlation, fp, was small at .04. Early sexual maturity was associated with higher rate of lay, whether rate of lay was determined for a partial year or for the entire period to 72 weeks of age. Early sexual m a t u r i t y was associated with lower albumen quality at 32 weeks of age. This result is undoubtedly a consequence of length of time in production. The genetic and phenotypic correlations between egg weight and body weight were positive and of about the same magnitude, but the environmental correlation was negative. Study of the individual year estimates revealed t h a t the latter m a y be due to an overestimate or fsd. The phenotypic correlation between egg weight and percent production to J a n u a r y 1 was — .02 one year and —.01 the next, while a much stronger negative genetic correla-
tion was found. At the same time f„ was highly positive. There was an indication t h a t maternal effects did not have the same negative relationship between egg weight and rate of production. This is even more obvious in the correlations between egg weight and percent production to 72 weeks of age. There was also a positive correlation between egg weight and rate of production to 72 weeks due to dominance effects. Body weights taken at 32 weeks of age were highly correlated with percent egg production to J a n u a r y 1 when measured as fs, but not so highly correlated when measured as fd- These positive genetic correlations, no doubt, are related to the physiological state of active reproduction with its concomitant increase in body weight, especially early in the productive year when only low producers are likely to be out of production. The genetic correlation due to dominance was negative, being —.26, while the environmental correlation was of about the same size, b u t positive a t .29. I t is interesting to note t h a t the genetic correlation with percent production to 72 weeks of age showed a marked reversal from its status at 32 weeks of age when it went from .70 to — .01 for fs and from .07 to .33 for fd. The correlation due to dominance and environment remained relatively unchanged, as did the phenotypic correlation. The genetic correlation between body weight and Haugh units—fresh was only .03 for fs, b u t fd was .31 indicating t h a t higher body weights were associated with higher Haugh units. Possible maternal effects had something to do with this result, but the fsd correlation of —1.95 m a y indicate a gross compensation error of the estimation process. Percent production to J a n u a r y 1 showed high genetic correlations with percent production to 72 weeks of age. The genetic
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these two traits. The estimate, rs
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TABLE 7.—Experimental verification of analytical procedure. {Correlation between egg weights taken alternate days) Year
f,
1957 1958
1.000 1.008
h 0.996 1.003
rSd
1.135 1.014
\
rv
0.285 0.465
0.935 0.933
CONCLUSIONS Having restored our confidence in the analytical methods utilized, if not the precision of many of our estimates, what general conclusions can be drawn and what implications do these hold for the practical breeder and research geneticist? First, the method of variance components analysis is a valuable tool in discovering what forms of genetic variation exist in a population, but large numbers of sires, dams and progeny are required in order to obtain estimates with any degree of reliability. For further discussion of this point see Robertson (1960). Estimates of heritability are much less likely to be outside the realm of possibility than are estimates of genetic correlation. It would appear that only the sires' component of variance can be utilized to estimate the additive genetic variance. Our results have demonstrated that even when the design of the experiment allows one to partition out the dominance portion of variance from the dams' components of variance, maternal effects apparently are much more widespread and of greater importance in adult traits than previously believed possible. Thus, the dams' component of variance is mainly useful in determining the magnitude of maternal effects, but then only when dominance effects have been partitioned out in the analysis. In the simpler nested design, where the sire by dam interaction cannot be estimated, too many different genetic sources of variation are confounded in the dams' component of variance to make it of much value. It is clear that the problem of constructing the most efficient breeding system is
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correlation between both estimates of percent production and Haugh unitsfresh were above —.3 except for an fsa of .69 for percent production to 72 weeks of age. These results were not in good agreement with the same traits correlated with June USDA albumen scores. This lack of agreement may well be due to the fact that many birds included in the early estimate of albumen quality failed to lay eggs for observation in June. Thus, the genetic sample could have been different or the smaller sample could have caused much less precision in the estimation procedure. In view of the extreme fluctuation in the estimates of genetic correlations, a procedure for verification of the analytical methods used seemed desirable. It so happened that in the course of securing data for the paper by King et al. (1961), two independent estimates of average egg weight were obtained for each bird. Since each of these egg weights was the average weight of eggs laid on six different days out of the same 12 day period following 32 weeks of age, it was hypothesized that they should be genetically identical. Each of the two egg weights utilized in the correlation analysis represented an average of 4.5 eggs per bird. Correlation analyses were done on both years' data. The results presented in Table 7 clearly demonstrate that our hypothesis was not. disproved, in fact, one could hardly anticipate coming this close to a perfect correlation of 1.0 for the six genetic correlations estimated. The deviation from
1.0 was greatest for both estimates of fsd, further emphasizing our earlier comments about the greater error inherent in our estimates of dominance.
INHERITANCE OF ECONOMIC TRAITS
assumption of certain limitations in facilities and budget. Robertson (1960) already has covered this problem from a theoretical point of view. There is no doubt that the population investigated, with its broad genetic base, has a great amount of genetic variation. Most of the heritability estimates were higher than those found in the literature, especially when one considers that most of the literature estimates contain variation due to maternal effects and dominance. Selection should be very effective for most of the traits analyzed. It is probable that this population is not indicative of the situation existing in closed flocks that have been selected for many years. However, this flock will provide much valuable information relative to changes in genetic parameters due to selection, when samples from the flock are subjected to various selection schemes. SUMMARY
Two years' data collected from the Regional Cornell Control population were available, where the mating scheme permitted an analysis in which sire by dam interaction variances could be estimated. Heritabilities (additive) of several economic traits were .26 for age at first egg, .62 for 32 week egg weight, .62 for 32 week body weight, .06 for percent production to January 1, .16 for percent production to 72 weeks of age, and .10 for USDA albumen score in June. Consistently higher estimates of heritability from dams' variance components indicated maternal effects of .08 for age at first egg, .03 for 32 week egg weight, .03 for 32 week body weight, .09 for percent production to January 1, .12 for percent production to 72 weeks and .15 for USDA albumen score in June. Dominance effects were important for several traits, being for age at first egg, .04, egg weight,
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more complex than most geneticists would like it to be. For example, age at first egg in the Regional Cornell Control population had a heritability in the additive sense of .26, a moderate maternal effect and little dominance, while 32 week egg weight had a high heritability of .60, small maternal effect and moderate dominance. At the same time, 32 week body weight had a high heritability with small maternal and dominance effects, yet percent production had a low heritability with high maternal and dominance effects. With the situation as complex as this it is unlikely that a single best breeding system exists, or at least it would be difficult to establish this fact, if one does exist. The best system for one trait is not best for another, so one must arrive at some sort of compromise. Our opinion, and it is only that, would be to select for specific combining ability for egg production and viability and do the major share of the selection for the other traits within each pure strain or breed involved in a strain or breed cross. We need to know more about the underlying cause of maternal effects before one can say whether one should give merits or demerits to superior dams. Basically, one would favor dams with good genetic mothering ability, but discredit dams who had good mothering ability via their environment. Some indication of the status of genetic correlations in this populations was obtained, but a great deal remains to be learned. There is little doubt that correlations do exist, some favorable and some unfavorable. Construction of selection indices require more reliable estimates of genetic correlations than we were able to obtain from these data. More emphasis needs to be given to the design of population structures that will yield the most satisfactory estimates of genetic correlations under the
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REFERENCES Bell, A. E., and C. H. Moore, 1958. Further comparisons of reciprocal recurrent selection with conventional methods of selection for the improvement of quantitative characteristics. Proc. X Int. Congress of Genetics, Vol. I I : 20-21. Chapman, A. B., 1946. Genetic and nongenetic sources of variation in the weight response of the immature rat ovary to a gonodotrophic hormone. Genetics, 3 1 : 494-507. Clayton, G. A., J. A. Morris and A. Robertson, 1957. An experimental check on quantitative genetical theory. I. Short-term responses to selection. J. Genetics, 55 : 131-151. Eisenhart, C , 1947. The assumptions underlying the analysis of variance. Biometrics, 3 : 1-21.
Hazel, L. N., and W. F. Lamoreux, 1947. Heritability, maternal effects and nicking in relation to sexual maturity and body weight in White Leghorns. Poultry Sci. 26: 508-514. Henderson, C. R., 1953. Estimation of variance and covariance components. Biometrics, 9: 226-252. Hutt, F. B., and R. K. Cole, 1955. Multiple shifts for testing cockerels. Poultry Sci. 34: 271-283. Jaap, R. G., and J. H. Smith, 1959. Selection for rapidity of growth. Poultry Sci. 38: 1215. Jerome, F. N., C. R. Henderson and S. C. King, 1956. Heritabilities, gene interactions, and correlations associated with certain traits in the domestic fowl. Poultry Sci. 35 : 995-1013. King, S. C , and C. R. Henderson, 1954. Heritability studies of egg production in the domestic fowl. Poultry Sci. 33: 15S-169. King, S. C , and J. D. Mitchell, 1959. Egg quality genetic variation and covariation. Poultry Sci. 38: 1218. King, S. C , J. D. Mitchell, W. H. Kyle and W. J. Stadelman, 1961. Egg quality genetic variation and covariation. Poultry Sci. 40: 965-975. Kyle, W. H., and J. D. Mitchell, 1958. Heritability of the change in egg quality during storage. Poultry Sci. 37: 1219. Martin, G. A., and A. E. Bell, 1960. An experimental check on the accuracy of prediction of response during selection. Biometrical Genetics, 178-187. Robertson, A., 1960. Experimental design in the evaluation of genetic parameters. Biometrics, 15: 219-226. Robertson, F. W., and E. C. R. Reeve, 1952. Studies in quantitative inheritance. I. The effects of selection of wing and thorax length in Drosophila melanogaster. J. Genetics, 50: 414-448. Smith, J. H., and R. G. Jaap, 1957. Non-additive genetic effects on growth in a flock closed from crossbred parents. Poultry Sci. 36: 1158.
NEWS AND NOTES (Continued from page 920) pursued. In 1959 to 1960 Dr. Sturkie was on leave from Rutgers, and served as a guest research worker at the Poultry Research Centre, Edinburgh, Scotland. In 1947 Dr. Sturkie received the Poultry Science Association Research Award, and in 1956, the Borden Award. He is a former Associate Editor of Poultry Science, a Fellow of the Royal Society of (Continued on page 1015)
Dr. Sturkie is the author of some 75 technical papers on the heart and circulation, physiology of reproduction, and other areas. His textbook, Avian Physiology, published in 1954 was the first comprehensive book in this area. He was instrumental in the organization of the research and teaching unit in avian physiology at Rutgers, where an active program in research and graduate work has been
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.24, body weight, .10, percent production to January 1, .36, percent production to 72 weeks, .36, and USDA albumen score, .08. Genetic correlations were not as consistent between years as heritabilities and more often exceeded the realm of possibility, especially the estimates due to dominance. The genetic correlations between egg weight and egg production and between egg production and albumen quality were negative. There was some evidence that genetic correlations due to additive effects, maternal effects or dominance were not necessarily of the same magnitude or even of the same sign. These results emphasize the complexity of the inheritance of economic traits and perhaps explain the difficulties which apparently have arisen in maintaining continued progress with selection programs.
EGG QUALITY VARIATION
able genetic variation in albumen quality loss. Our genetic correlations indicated that early sexual maturity is associated with lower egg quality. Similarly, consistent negative correlations between egg production and egg quality were found. REFERENCES
Inheritance of Economic Traits in the Regional Cornell Control Population 1 STEVEN C. K I N G 2
Poultry Research Branch, Animal Husbandry Research Division, ARS, Regional Breeding Laboratory, Purdue University, Lafayette, Indiana
Poultry
(Received for publication September 19, 1960)
K
NOWLEDGE of genetic parameters is useful in designing efficient breeding systems. Estimation of genetic parameters raises the problem of suitable material as a source of data. Until recently, genetic pa1 This investigation was conducted as a portion of the cooperative research of the NC-47 Regional Poultry Breeding Project, entitled, "Evaluation of Breeding Systems for Chickens." 2 Present address: Poultry Research Branch, Animal Husbandry Research Division, Beltsville, Maryland.
rameters in poultry populations have been estimated from data collected from inbred lines or selected populations. Estimates obtained from inbred lines have required correction factors in order to compensate for changes in genetic variance due to inbreeding. In addition, few of these inbred lines were developed without considerable natural and/or artificial selection. Estimates obtained from non-inbred populations under artificial selection have ignored, for the most part, the bias which may result from
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Eisenhart, C , 1947. The assumptions underlying the analysis of variance. Biometrics, 3 : 1-21. Goodman, B. L., and G. F. Godfrey, 1955. Genetic, phenotypic and environmental correlations between some egg quality traits and egg production and hatchability. Poultry Sci. 34: 1197. Henderson, C. R., 1953. Estimation of variance and covariance components. Biometrics, 9: 226-252. Jerome, F. N., C. R. Henderson and S. C. King, 1956. Heritabilities, gene interactions, and correlations associated with certain traits in the domestic fowl. Poultry Sci. 35: 995-1013. Johnson, A. S., and E. S. Merritt, 1955. Heritability of albumen height and specific gravity of eggs from White Leghorns and Barred Rocks and the correlations of these traits with egg production. Poultry Sci. 34: 578-587.
King, S. C , 1961. Inheritance of economic traits in the Regional Cornell Control population. Poultry Sci. 40: 975-986. King, S. C, J. R. Carson and D. P. Doolittle, 1959. The Connecticut and Cornell randombred populations of chickens. World's Poultry Sci. J. 15: 139-159. King, S. C , and G. 0. Hall, 1955. Egg quality studies at the New York Random Sample Test. Poultry Sci. 34: 799-809. King, S. C , and C. R. Henderson, 1954. Variance components analysis in heritability studies. Poultry Sci. 33 : 147-154. Kyle, W. H., and J. D. Mitchell, 1958. Heritability of the change in egg quality during storage. Poultry Sci. 37: 1219. May, K. N., F. J. Schmidt and W. J. Stadelman, 1957. Strain variation in albumen quality decline of hen's eggs. Poultry Sci. 36: 1376-1379. McClary, C. F., and G. E. Bearse, 1956. The genetic correlation of albumen quality in fresh and stored eggs. Poultry Sci. 35: 1157. Mueller, W. J., 1959. Factors affecting the quality loss in egg albumen during storage. Poultry Sci. 38: 843-846. Yao, K. T. S., 1958. Egg interior quality of purebred, inbred, incross and incrossbred chickens. Poultry Sci. 37: 1254-1255.
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and Mitchell (1959) and King et d, (1961) meet the necessary assumptions for a variance components analysis. The purpose of this paper is to report the results of our analysis of data collected from the Regional Cornell Control population of White Leghorns, which is maintained at the Regional Poultry Breeding Laboratory, Lafayette, Indiana. Several of the economic traits of importance in egg production stocks were analyzed. MATERIALS AND METHODS Many estimates of genetic parameters in the domestic fowl have been reported in the literature, but relatively few have resulted from experimental designs which enabled estimates of sire by dam interactions to be made. Hazel and Lamoreux (1947) published estimates of dominance as did Jerome, Henderson and King (1956) much later. Since then Smith and Jaap (1957) have indicated some of the problems involved in achieving reliable estimates. Jaap collected data from diallel sets of matings, each of which yielded one degree of freedom for the sire by dam interaction mean square. He later tried, with some success, triallel sets in order to build up degrees of freedom at a faster rate and to achieve estimates having narrower confidence limits. Devising a mating scheme for animals, which will result in data that fit a neat analysis of sire by dam interaction effects, is no small problem. It is a simple matter with economic species of farm animals and birds to mate a single male to several females, either naturally or through artificial insemination. However, the physiology of reproduction of the female of these species make it extremely difficult to mate a female to several males at the same time and still maintain the identity of the male parent. It is possible to accomplish this feat through the use of a different marker gene for each male parent, but this, for all
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the use of selected parents in the typical variance components analysis. Correction for the reduction of genetic variance in selected parents by the use of adjustment factors is very difficult or even not feasible with the accuracy one desires. Even when selection is for only one or a few traits, correlated responses may introduce some bias into the estimates of the parameters of traits not selected. While it is not intended to imply that genetic parameters estimated in selected populations do not have value, the usual variance components analysis assumes unselected parents mated at random. Further, an understanding of the fundamental genetic forces coming into play would appear to be somewhat easier to achieve without the complicating effects of selection and inbreeding. The several randombred control populations, which have been established at various institutions, furnish an excellent opportunity to secure data from offspring of unselected parents. Another advantage of utilizing material of this kind is the opportunity of observing changes in genetic parameters when a subsample of the control population is put under a selection system. This has obvious advantages over trying to extrapolate backwards, in order to determine what the genetic parameters might have been in a selected population before selection began. Estimates of genetic parameters have been published from research with pilot organisms by Chapman (1946), Robertson and Reeve (1952), Clayton, Morris and Robertson (1957), Bell and Moore (1958) and Martin and Bell (1960), to name a few, in which the data seem to satisfy the assumptions required in order to make an analysis of variance. With poultry as the experimental animal, only the data used by Smith and Jaap (1957), Jaap and Smith (1959), Kyle and Mitchell (1958), King
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T A B L E 1.—Example of mating plan showing the sire by dam subclass totals (same as sire by dam by shift totals) Dams/ Sires 1 2 3 4 5 O 7 8 Sire totals
1
l
Xni X112 X213
7
L
J
5
X231 X123 X124 X225
X234 X135 X136
X21S X.2..
X.3..
Dam totals
X246 X147 X148
X . . 1. X . .Z. X. .3. X..4. X..5. X. .6. X . .7. X. .8.
X.4..
X...
X242
X227
X.I..
i *
Shift t o t a l s = X I . . . a n d X 2 . . .
ing procedure was utilized, in which the same 50 males and 250 females were mated in two shifts, but a different randomization each shift was used to assign each male his 5 female mates. Thus, each male was mated to a total of ten females and each female was mated to two cockerels during the breeding season. In order to illustrate the mating plan and facilitate the presentation of the method of analysis utilized, an example is presented in Table 1 showing the smallest subclass totals. Note particularly that sire by dam subclasses are identical with sire by dam by shift subclasses, since a dam can be mated to only one sire at a time and still maintain the identity of the male parent. • Eggs for setting were saved for a two week period and pedigreed to both dam and sire. A minimum of two weeks elapsed from rerandomization of matings for the second shift and the beginning of egg saving again. In 1957 there was a period of seven weeks between first and second shift hatches, while in 1958 this period between shifts was four weeks. Enough pullets were banded so that approximately two progeny per dam could be housed in each shift. Traits considered in this paper include age at first egg, percent hen day egg production to January 1 (approximately 36-40
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practical purposes, precludes the collection of data from a closed flock. The domestic fowl is one of the few economic species in which it is possible to arrange successive matings with a rather short span of time elapsing between matings and still maintain the identity of the parents. Hutt and Cole (1955) describe procedures for reducing this time interval between matings, which result in relatively few paternity errors. Unfortunately, the device of shifting sires results in the elapse of approximately four weeks between hatches when eggs are saved two weeks before setting. Data collected from progeny hatched on different hatch dates may be influenced by environmental differences between hatches and also by genotype by environment interactions. The complexity of the statistical analyses can be kept to a minimum by saving eggs two weeks before setting, thus assuring that most dams have progeny in each hatch or shift. It is obvious that mating each dam to more than two or three sires will result in an extended series of shifts, each at least four weeks apart. Thus, the greater the number of sires mated to each dam, the more likely is the prospect of serious shift by dam interactions becoming confounded with sire by dam interactions. The genetic parameter estimates reported in this paper were obtained by analysis of data collected on pullet flocks of the Regional Cornell Control population hatched in 1957 and 1958. This population was established as a replication of the Cornell Randombred Control population in 1956, when pedigreed hatching eggs were obtained. Details on the development and maintenance procedures utilized for this population may be found elsewhere (King, Carson and Doolittle, 1959). The pullets from which these data were collected were the progeny of at least 50 single male matings each year. A sire shift-
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KING
TABLE 2.—Typical analysis of variance for sire'Kshift or hatch interaction Source Shift or hatch Sires Shift & Sires Dams w/n sires & shift Fullsibs
E(d. f.)
Actual d. f.
a —I s— 1 (a-l)(s-l) as(d — 1) ad(n-l)
1 50 48 197 490
E(m. s.)
£i = 2.45, ^ 2 = 2.86
ls.+ah+Si+dj-\-{sd)ij-\&h ijk
where /x is common to all observations, ah to all pullets in the hth shift (also hatch in this case, since there is only one hatch per shift), Si to all observations from the ith sire, dj to all records made by progeny of the j t h dam, {sd)ij to all records made by full sib progeny of the ith sire and j t h dam. Peculiar to each observation is the random error eujk- I t is assumed t h a t except for n, all elements of the model are uncorrelated variables with zero means and variances
period of seven weeks elapsed between shifts or hatches. If such an interaction variance exists in our data, it would have the greatest opportunity to express itself when the time difference between hatches was greatest, there being a greater likelihood of a significant hatch effect. The same experimental plan and set of data were utilized, but a different statistical model was employed. This was possible because of the unique nature of the breeding program used in the Regional Cornell Control flock. For this analysis the model, Yijki =
ii-\-ai+Sj-\-djkJr{as)ij+eijki
was assumed, where n is common to all observations, ff; to the tth hatch or shift, Sj to t h e j t h sire, djk to the kih dam within the j t h sire, (as)a to the interaction between the i t h hatch and j t h sire and e^u is the random error associated with each individual observation. Note t h a t under this model, any interaction between sire and dam,
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weeks of age) and at 72 weeks of age, 32 week body weight, 32 week egg weight and albumen score in June. An analysis of fresh and stored albumen quality at 32 weeks of age was presented in King et al. (1961). The statistical analyses utilized in this paper were based on the assumption of the linear model:
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TABLE 3.—Mean squares for testing significance of shift by sire interaction for several traits Dam w/n sires
Trait
Shift by sires
19.42 30.59 40.64 56.65 20.09 5.18
Haugh unit loss % Stored of fresh H. U. Haugh units, fresh Haugh units, stored Egg weight Total eggs (12 days)
16.54 22.60 38.27 37.08 19.10 4.25
and the coefficients of their expectations. Since high speed electronic computer equipment was available, the expectations in terms of sums of "squares were utilized. These were equated to the sums of squares and upon solving, the resulting equations yielded estimates of ju2, aj, o's2, a£, usi and o-„2. The discussion presented in King et al. (1961), pertaining to genetic parameters contained in each of the foregoing variances, applies equally to this paper. As in that paper, the term dominance is utilized to describe the genetic variance in the sire by dam interaction even though some other non-additive variance may be present. RESULTS AND DISCUSSION
Heritability estimates, presented in Table 4, are given by trait, year and
TABLE 4.—Estimates of heritability, environment, variance and means
i2
Trait Age at 1st Egg
1957 1958 Av.
32 Wk. Egg Wt.
1957 1958 Av. 1957 1958 Av.
32 Wk. Body Wt.
% Prod, to Jan. 1
1957 1958 Av.
% Prod, to 72 Wks.* USDA Albumen Score—June*
1957 1957
0.33 0.19 0.26 0.63 0.58 0.60 0.67 0.57 0.62 0.14 -0.02 0.06 0.16 0.10
V
hi
hj
h*
0.62 0.52 0.57
0.11 -0.02 0.04 0.16 0.32 0.24 0.24 -0.03 0.10
0.45 0.66 0.56
5.11 5.76 5.44
0.08 0.11 0.10 0.00 0.43 0.21
15.27 13.07 14.17 0.216 0.277 0.246
4.02 lbs. 4.04 lbs. 4.03 lbs.
0.44 0.29 0.36 0.36
0.24 0.53 0.38
245.5 254.4 250.0
72.6 74.3 73.4
0.24 0.51
292.3 0.976
66.3 4.06
0.88 0.58 0.73 0.86 0.63 0.74 0.49 0.37 0.43 0.64 0.71
0.08
* Analyses were completed before data for these traits had been collected in 1959.
X
25.85 wks. 26.22 wks. 26.04 wks. 52.7 gr. 52.0 gr. 52.4 gr.
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mean square for dams within sires and shifts in order to make a valid test of significance. Results presented in Table 3 indicate that F ratios would be less than one for each trait analyzed for shift by sire interaction. Clearly, the assumption of no shift by sire interaction appears to be tenable in this set of data. It would appear to be quite reasonable, then, to assume that the shift by dam interaction would be similarly unimportant, although one must admit that maternal effects due to health differences among the dams conceivably could change between shifts. The high production of the breeder flocks would not indicate this to be the case in this experiment. Having demonstrated that our assumption of no shift by sire interaction appears to be valid and assuming the unlikelihood of a shift by dam interaction, let us return to further consideration of the analysis of variance procedure utilized in order to produce the required sums of squares and cross products. The assumptions outlined correspond to those of the Eisenhart (1947) Model II. Henderson's (1953) Method 1 is an appropriate procedure for computing the sums of squares
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TABLE 5.—Maternal effects Trait Age at 1st Egg 32 Wk. Egg Wt. 32 Wk. Body Wt. % Prod, to Jan. 1 % Prod, to 72 Wks. USDA Alb. Score
1957
1958
Av.
0.072 0.062 0.048 0.088 0.120 0.152
0.082 0.000 0.015 0.098
0.077 0.031 0.032 0.093 0.120 0.152
— —
parable to those published by Hazel and Lamoreux (1947) for body weight, b u t they found no maternal effect for sexual maturity, while our data resulted in an estimate of 7.7%. To our knowledge maternal effects have not been estimated by other investigators. Even though our estimates indicate t h a t maternal effects are small, the fact t h a t they were consistently present forces one to consider the consequences of their presence in a selection program. I t is of no little importance to know whether these maternal effects are due to genetic differences or chance environmental influences t h a t made some hens better dams than others. Selection based on dam family averages would be highly desirable in the instance of genetic differences, but if these differences are due to environmental effects, one would want to discount in some way those dams which appeared to be the best. These results are all the more surprising in an oviparous species. Everyone is familiar with the important effect the mother may have on her young in mammalian species, where the nutrition and protection may extend from a few weeks to m a n y months depending upon the species. Even after birth the mother m a y continue to exert a great influence on her offspring before it is weaned. In the domestic fowl the hen must be content to rely on what she included in the egg, because she ceases to have any further opportunity under today's commercial conditions. These small, but consistent, maternal effects, found for each of six important productive traits suggest a whole new field of research. Included in the knowledge we would like to have is the extent to which the environment of the mother m a y be modified to improve the performance of her progeny, the mechanisms by which maternal effects are passed through the egg to influence prog-
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source of the estimate of genetic variance. A rather striking feature of these estimates of heritability is the fact t h a t the estimates utilizing the dam's component of variance are in every instance as large as or larger t h a n the estimates from sire components. These results are of considerable importance, because the method of analysis has partitioned out a component of variance due to sire by dam interaction. Recall t h a t except for a limited number of estimates reported in the literature, the dam's component in the hierarchial classification includes any existing sire by dam interaction. With the exception of a few instances, the estimates of heritability from dams' components of variance has been higher than estimates from the sires' components of variance. Because of confounding it has been impossible to say whether maternal effects, sire by dam interactions or both have been responsible for the higher estimates from dams' components. Since our analysis partitioned out the sire by dam interaction variance component, we must conclude t h a t maternal effects were present for each trait in our analysis. While the fairly large differences between heritability estimates from sire and dam components make maternal effects appear to be of considerable magnitude, there is a multiplication factor of 4 included in the estimation procedure. Thus, the maternal effects, as shown in Table 5, are not particularly large even though they are fairly consistent in their presence. Our estimates of maternal effects are quite com-
KING
INHERITANCE OF ECONOMIC TRAITS
Egg weight, with an hs2 of 0.60, had a very high heritability and the estimate of 0.73 for hi indicated a small, but inconsistent, maternal effect. Surprising was the estimate of 0.24 for hsd2. With such a high estimate for additive variation one doesn't expect to see as much dominance, but it appears that the environment, accounting for only 10 percent of the total, had little to do with egg weight variation within hatches. Body weight showed the same high heritability as egg weight. It is evident
that the genetic variation is overestimated in the 1957 data, since one hardly can imagine a population in which the environment contributed nothing to body weight variation. Again there was some evidence for dominance effects for body weight, but the estimates weren't consistent between years. Heritability of egg production to January first was low and maternal effects appear to be at least as important in the total variation. Our hsi at 0.36 lends considerable support to the idea that dominance variation is a factor of importance in dealing with the inheritance of egg production. These results show quite clearly that the usual dams within sires nested classification may lead to gross overestimates of additive variation, when estimated by the &i component. When the production period was extended to 72 weeks of age, the results were about the same except that, astonishingly enough, maternal effects seemed to be even more important than for the part record. Whether this could come about through differences in maternal immunity passed through the egg and operating over a longer period or other mechanisms, we cannot say. Note that June albumen score, taken near the end of the laying year, exhibits a similar effect. The generally higher heritability estimates reported here as compared to those found in the literature deserve some comment. The Regional Cornell Control population was established with a broad genetic base. There has been no artificial selection and natural selection has been minimized. Inbreeding has been avoided, thus emulating an infinite population where inbreeding is zero. All these factors have tended to maintain the original high variability, thus one should expect higher heritabilities than those reported in the literature from various closed flocks and
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eny performance months later, and the extent and nature of the adjustments that may be required in selection programs. The average heritability for age at first egg, presented in Table 4, was 0.26 and 0.57 when estimated by hs2 and hi respectively. The difference of 0.31 can be explained by a maternal effect of only 0.077, discussed previously. It must be acknowledged that if sex-linked effects exist, they would cause the difference between hi and hi to be smaller, thus underestimating maternal effects. Since hi includes both additive variation and sex-linked effects, one is more or less forced to assume that hi is an upper limit for heritability in the additive sense and, until such time as conclusive evidence of sex-linked effects is forthcoming, that hi is the best point estimate available. Our 0.26 is identical with the average of published estimates reported by King and Henderson (1954), but in reality probably is an estimate of a higher parameter, because the earlier average included estimates that undoubtedly were inflated by maternal and dominance effects included in the estimation procedures. Apparently sexual maturity is but little influenced by dominance effects, however, since h3i was only 0.04 in our data with a small positive estimate the first year being partially offset by a slightly negative estimate the second year.
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S. C. KING TABLE 6.—Estimates of genetic, environmental and phenotypic correlations averaged overthe Z years
Age at 1st egg and 32 Wk. Egg Wt. 32 Wk. Body Wt. % Prod, to Jan. 1 % Prod, to 72 Wks. Haugh Units—Fresh
r*
Td
rsd
rCl
r?
0.78 0.50 -0.15 -0.17 0.40
0.13 -0.08 -0.80 -1.07 0.33
-2.05 -1.66 -0.25 1.73 -1.59
0.62 0.18 0.13 -0.68 0.41
0.13 0.04 -0.18 -0.23 0.23
0.33 -0.50 -0.24 0.30
0.57 -0.06 0.26 0.32
1.05 -0.35 0.21 -1.48
-0.40 0.78 0.03 1.18
0.40 -0.02 0.11 0.12
0.70 -0.01 0.03
0.07 0.33 0.31
-0.26 -0.32 -1.95
0.29 0.24 0.52
0.13 0.09 0.03
0.69 -0.33
1.11 -0.34
0.39 -0.38
0.49 0.21
0.64 -0.13
-0.30 0.34
-0.45 -0.20
0.69 1.53
0.00 -0.57
-0.06 0.02
32 Wk Egg Wt. and
32 Wk. Body Wt. and % Prod, to Jan. 1 % Prod, to 72 Wks. Haugh Units—Fresh % Prod, to Jan. 1 and % Prod, to 72 Wks. Haugh Units—Fresh % Prod, to 72 Wks. and Haugh Units—Fresh USDA Alb. Score
* rs is an estimate computed from sire covariances and variances, "n from dam covariances and variances, and fSd from sireXdam covariances and variances.
inbred lines established from these flocks, which had variation reduced by both selection and inbreeding. A survey of the genetic correlations reported in Table 6 lead one to the conclusion t h a t their estimation is far from satisfactory from the point of view of consistency. The situation doesn't appear to be quite as hopeless, if one remembers the previous discussion of maternal effects and the fact t h a t they are included in the d a m s ' component of variance. Certainly, there is no logical reason to believe t h a t correlations due to maternal effects must necessarily be of the same magnitude, or even of the same sign, as those due to additive variation. Also, it follows t h a t correlations due to dominance deviations need not be necessarily of the same magnitude or sign as those due to additive deviations. However, even after making
allowances for these considerations, it is evident from Table 6 t h a t correlations due to dominance effects often exceed the theoretical limits and to a lesser extent this is true for correlations computed from dams' components of variance and covariance. I n spite of these difficulties, there are some observations from which one m a y draw tentative conclusions or perhaps suggest the existence of certain trends. For the author, at least, consideration of the estimates of heritabilities in Table 4 has helped to interpret or rationalize the correlations presented in Table 6. Early sexual maturity appears to be associated with small egg size whether one is thinking in terms of genetic correlations due to additive effects or environmental effects; however, environmental effects played a large part in the relationship between
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32 Wk. Body Wt. % Prod, to Jan. 1 % Prod, to 72 Wks. Haugh Units—Fresh
INHERITANCE OF ECONOMIC TRAITS
Early sexual m a t u r i t y was associated with small body size when the genetic correlation was estimated by f„ but fd was —.08, indicating t h a t maternal effects may have been in the opposite direction. The phenotypic correlation, fp, was small at .04. Early sexual maturity was associated with higher rate of lay, whether rate of lay was determined for a partial year or for the entire period to 72 weeks of age. Early sexual m a t u r i t y was associated with lower albumen quality at 32 weeks of age. This result is undoubtedly a consequence of length of time in production. The genetic and phenotypic correlations between egg weight and body weight were positive and of about the same magnitude, but the environmental correlation was negative. Study of the individual year estimates revealed t h a t the latter m a y be due to an overestimate or fsd. The phenotypic correlation between egg weight and percent production to J a n u a r y 1 was — .02 one year and —.01 the next, while a much stronger negative genetic correla-
tion was found. At the same time f„ was highly positive. There was an indication t h a t maternal effects did not have the same negative relationship between egg weight and rate of production. This is even more obvious in the correlations between egg weight and percent production to 72 weeks of age. There was also a positive correlation between egg weight and rate of production to 72 weeks due to dominance effects. Body weights taken at 32 weeks of age were highly correlated with percent egg production to J a n u a r y 1 when measured as fs, but not so highly correlated when measured as fd- These positive genetic correlations, no doubt, are related to the physiological state of active reproduction with its concomitant increase in body weight, especially early in the productive year when only low producers are likely to be out of production. The genetic correlation due to dominance was negative, being —.26, while the environmental correlation was of about the same size, b u t positive a t .29. I t is interesting to note t h a t the genetic correlation with percent production to 72 weeks of age showed a marked reversal from its status at 32 weeks of age when it went from .70 to — .01 for fs and from .07 to .33 for fd. The correlation due to dominance and environment remained relatively unchanged, as did the phenotypic correlation. The genetic correlation between body weight and Haugh units—fresh was only .03 for fs, b u t fd was .31 indicating t h a t higher body weights were associated with higher Haugh units. Possible maternal effects had something to do with this result, but the fsd correlation of —1.95 m a y indicate a gross compensation error of the estimation process. Percent production to J a n u a r y 1 showed high genetic correlations with percent production to 72 weeks of age. The genetic
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these two traits. The estimate, rs
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TABLE 7.—Experimental verification of analytical procedure. {Correlation between egg weights taken alternate days) Year
f,
1957 1958
1.000 1.008
h 0.996 1.003
rSd
1.135 1.014
\
rv
0.285 0.465
0.935 0.933
CONCLUSIONS Having restored our confidence in the analytical methods utilized, if not the precision of many of our estimates, what general conclusions can be drawn and what implications do these hold for the practical breeder and research geneticist? First, the method of variance components analysis is a valuable tool in discovering what forms of genetic variation exist in a population, but large numbers of sires, dams and progeny are required in order to obtain estimates with any degree of reliability. For further discussion of this point see Robertson (1960). Estimates of heritability are much less likely to be outside the realm of possibility than are estimates of genetic correlation. It would appear that only the sires' component of variance can be utilized to estimate the additive genetic variance. Our results have demonstrated that even when the design of the experiment allows one to partition out the dominance portion of variance from the dams' components of variance, maternal effects apparently are much more widespread and of greater importance in adult traits than previously believed possible. Thus, the dams' component of variance is mainly useful in determining the magnitude of maternal effects, but then only when dominance effects have been partitioned out in the analysis. In the simpler nested design, where the sire by dam interaction cannot be estimated, too many different genetic sources of variation are confounded in the dams' component of variance to make it of much value. It is clear that the problem of constructing the most efficient breeding system is
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correlation between both estimates of percent production and Haugh unitsfresh were above —.3 except for an fsa of .69 for percent production to 72 weeks of age. These results were not in good agreement with the same traits correlated with June USDA albumen scores. This lack of agreement may well be due to the fact that many birds included in the early estimate of albumen quality failed to lay eggs for observation in June. Thus, the genetic sample could have been different or the smaller sample could have caused much less precision in the estimation procedure. In view of the extreme fluctuation in the estimates of genetic correlations, a procedure for verification of the analytical methods used seemed desirable. It so happened that in the course of securing data for the paper by King et al. (1961), two independent estimates of average egg weight were obtained for each bird. Since each of these egg weights was the average weight of eggs laid on six different days out of the same 12 day period following 32 weeks of age, it was hypothesized that they should be genetically identical. Each of the two egg weights utilized in the correlation analysis represented an average of 4.5 eggs per bird. Correlation analyses were done on both years' data. The results presented in Table 7 clearly demonstrate that our hypothesis was not. disproved, in fact, one could hardly anticipate coming this close to a perfect correlation of 1.0 for the six genetic correlations estimated. The deviation from
1.0 was greatest for both estimates of fsd, further emphasizing our earlier comments about the greater error inherent in our estimates of dominance.
INHERITANCE OF ECONOMIC TRAITS
assumption of certain limitations in facilities and budget. Robertson (1960) already has covered this problem from a theoretical point of view. There is no doubt that the population investigated, with its broad genetic base, has a great amount of genetic variation. Most of the heritability estimates were higher than those found in the literature, especially when one considers that most of the literature estimates contain variation due to maternal effects and dominance. Selection should be very effective for most of the traits analyzed. It is probable that this population is not indicative of the situation existing in closed flocks that have been selected for many years. However, this flock will provide much valuable information relative to changes in genetic parameters due to selection, when samples from the flock are subjected to various selection schemes. SUMMARY
Two years' data collected from the Regional Cornell Control population were available, where the mating scheme permitted an analysis in which sire by dam interaction variances could be estimated. Heritabilities (additive) of several economic traits were .26 for age at first egg, .62 for 32 week egg weight, .62 for 32 week body weight, .06 for percent production to January 1, .16 for percent production to 72 weeks of age, and .10 for USDA albumen score in June. Consistently higher estimates of heritability from dams' variance components indicated maternal effects of .08 for age at first egg, .03 for 32 week egg weight, .03 for 32 week body weight, .09 for percent production to January 1, .12 for percent production to 72 weeks and .15 for USDA albumen score in June. Dominance effects were important for several traits, being for age at first egg, .04, egg weight,
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more complex than most geneticists would like it to be. For example, age at first egg in the Regional Cornell Control population had a heritability in the additive sense of .26, a moderate maternal effect and little dominance, while 32 week egg weight had a high heritability of .60, small maternal effect and moderate dominance. At the same time, 32 week body weight had a high heritability with small maternal and dominance effects, yet percent production had a low heritability with high maternal and dominance effects. With the situation as complex as this it is unlikely that a single best breeding system exists, or at least it would be difficult to establish this fact, if one does exist. The best system for one trait is not best for another, so one must arrive at some sort of compromise. Our opinion, and it is only that, would be to select for specific combining ability for egg production and viability and do the major share of the selection for the other traits within each pure strain or breed involved in a strain or breed cross. We need to know more about the underlying cause of maternal effects before one can say whether one should give merits or demerits to superior dams. Basically, one would favor dams with good genetic mothering ability, but discredit dams who had good mothering ability via their environment. Some indication of the status of genetic correlations in this populations was obtained, but a great deal remains to be learned. There is little doubt that correlations do exist, some favorable and some unfavorable. Construction of selection indices require more reliable estimates of genetic correlations than we were able to obtain from these data. More emphasis needs to be given to the design of population structures that will yield the most satisfactory estimates of genetic correlations under the
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REFERENCES Bell, A. E., and C. H. Moore, 1958. Further comparisons of reciprocal recurrent selection with conventional methods of selection for the improvement of quantitative characteristics. Proc. X Int. Congress of Genetics, Vol. I I : 20-21. Chapman, A. B., 1946. Genetic and nongenetic sources of variation in the weight response of the immature rat ovary to a gonodotrophic hormone. Genetics, 3 1 : 494-507. Clayton, G. A., J. A. Morris and A. Robertson, 1957. An experimental check on quantitative genetical theory. I. Short-term responses to selection. J. Genetics, 55 : 131-151. Eisenhart, C , 1947. The assumptions underlying the analysis of variance. Biometrics, 3 : 1-21.
Hazel, L. N., and W. F. Lamoreux, 1947. Heritability, maternal effects and nicking in relation to sexual maturity and body weight in White Leghorns. Poultry Sci. 26: 508-514. Henderson, C. R., 1953. Estimation of variance and covariance components. Biometrics, 9: 226-252. Hutt, F. B., and R. K. Cole, 1955. Multiple shifts for testing cockerels. Poultry Sci. 34: 271-283. Jaap, R. G., and J. H. Smith, 1959. Selection for rapidity of growth. Poultry Sci. 38: 1215. Jerome, F. N., C. R. Henderson and S. C. King, 1956. Heritabilities, gene interactions, and correlations associated with certain traits in the domestic fowl. Poultry Sci. 35 : 995-1013. King, S. C , and C. R. Henderson, 1954. Heritability studies of egg production in the domestic fowl. Poultry Sci. 33: 15S-169. King, S. C , and J. D. Mitchell, 1959. Egg quality genetic variation and covariation. Poultry Sci. 38: 1218. King, S. C , J. D. Mitchell, W. H. Kyle and W. J. Stadelman, 1961. Egg quality genetic variation and covariation. Poultry Sci. 40: 965-975. Kyle, W. H., and J. D. Mitchell, 1958. Heritability of the change in egg quality during storage. Poultry Sci. 37: 1219. Martin, G. A., and A. E. Bell, 1960. An experimental check on the accuracy of prediction of response during selection. Biometrical Genetics, 178-187. Robertson, A., 1960. Experimental design in the evaluation of genetic parameters. Biometrics, 15: 219-226. Robertson, F. W., and E. C. R. Reeve, 1952. Studies in quantitative inheritance. I. The effects of selection of wing and thorax length in Drosophila melanogaster. J. Genetics, 50: 414-448. Smith, J. H., and R. G. Jaap, 1957. Non-additive genetic effects on growth in a flock closed from crossbred parents. Poultry Sci. 36: 1158.
NEWS AND NOTES (Continued from page 920) pursued. In 1959 to 1960 Dr. Sturkie was on leave from Rutgers, and served as a guest research worker at the Poultry Research Centre, Edinburgh, Scotland. In 1947 Dr. Sturkie received the Poultry Science Association Research Award, and in 1956, the Borden Award. He is a former Associate Editor of Poultry Science, a Fellow of the Royal Society of (Continued on page 1015)
Dr. Sturkie is the author of some 75 technical papers on the heart and circulation, physiology of reproduction, and other areas. His textbook, Avian Physiology, published in 1954 was the first comprehensive book in this area. He was instrumental in the organization of the research and teaching unit in avian physiology at Rutgers, where an active program in research and graduate work has been
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.24, body weight, .10, percent production to January 1, .36, percent production to 72 weeks, .36, and USDA albumen score, .08. Genetic correlations were not as consistent between years as heritabilities and more often exceeded the realm of possibility, especially the estimates due to dominance. The genetic correlations between egg weight and egg production and between egg production and albumen quality were negative. There was some evidence that genetic correlations due to additive effects, maternal effects or dominance were not necessarily of the same magnitude or even of the same sign. These results emphasize the complexity of the inheritance of economic traits and perhaps explain the difficulties which apparently have arisen in maintaining continued progress with selection programs.